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AWS::CleanRooms::AnalysisTemplate MLSyntheticDataParameters
Parameters that control the generation of synthetic data for machine learning, including privacy settings and column classification details.
Syntax
To declare this entity in your CloudFormation template, use the following syntax:
JSON
{ "ColumnClassification" :ColumnClassificationDetails, "Epsilon" :Number, "MaxMembershipInferenceAttackScore" :Number}
YAML
ColumnClassification:ColumnClassificationDetailsEpsilon:NumberMaxMembershipInferenceAttackScore:Number
Properties
ColumnClassification-
Classification details for data columns that specify how each column should be treated during synthetic data generation.
Required: Yes
Type: ColumnClassificationDetails
Update requires: Replacement
Epsilon-
The epsilon value for differential privacy when generating synthetic data. Lower values provide stronger privacy guarantees but may reduce data utility.
Required: Yes
Type: Number
Minimum:
0Maximum:
10Update requires: Replacement
MaxMembershipInferenceAttackScore-
The maximum acceptable score for membership inference attack vulnerability. Synthetic data generation fails if the score for the resulting data exceeds this threshold.
Required: Yes
Type: Number
Minimum:
0Maximum:
1Update requires: Replacement
